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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Sains dan Teknologi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Teknik dan Ilmu Komputer Journal of ICT Research and Applications JUITA : Jurnal Informatika Scientific Journal of Informatics Jurnal Teknik Mesin JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Turbo : Jurnal Program Studi Teknik Mesin Techne : Jurnal Ilmiah Elektroteknika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Aptisi Transactions on Technopreneurship (ATT) Jurnal Pengabdian Masyarakat Ilmu Keguruan dan Pendidikan (JPM-IKP) Jurnal Pengabdian Masyarakat Bumi Raflesia Computer Science and Information Technologies Jurnal Darma Agung JUNCTO: Jurnal Ilmiah Hukum Jurnal Pengabdian kepada Masyarakat Nusantara ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Jurnal Bisnis, Logistik dan Supply Chain Jurnal Pengabdian Teratai Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Makara Journal of Technology Scientific Journal of Informatics
Iwan Setyawan
Universitas Kristen Satya Wacana
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Exploring network security threats through text mining techniques: a comprehensive analysis Tri Wahyuningsih; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
Computer Science and Information Technologies Vol 4, No 3: November 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i3.p258-267

Abstract

In response to the escalating cybersecurity threats, this research focuses on leveraging text mining techniques to analyze network security data effectively. The study utilizes user-generated reports detailing attacks on server networks. Employing clustering algorithms, these reports are grouped based on threat levels. Additionally, a classification algorithm discerns whether network activities pose security risks. The research achieves a noteworthy 93% accuracy in text classification, showcasing the efficacy of these techniques. The novelty lies in classifying security threat report logs according to their threat levels. Prioritizing high-risk threats, this approach aids network management in strategic focus. By enabling swift identification and categorization of network security threats, this research equips organizations to take prompt, targeted actions, enhancing overall network security.
Number of Cyber Attacks Predicted With Deep Learning Based LSTM Model Joko Siswanto; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.20210

Abstract

The increasing number of cyber attacks will result in various damages to the functioning of technological infrastructure. A prediction model for the number of cyber attacks based on the type of attack, handling actions and severity using time-series data has never been done. A deep learning-based LSTM prediction model is proposed to predict the number of cyberattacks in a time series on 3 evaluated data sets MSLE, MSE, MAE, RMSE, and MAPE, and displays the predicted relationships between prediction variables. Cyber attack dataset obtained from kaggle.com. The best prediction model is epoch 20, batch size 16, and neuron 32 with the lowest evaluation value on MSLE of 0.094, MSE of 9.067, MAE of 2.440, RMSE of 3.010, and MAPE of 10.507 (very good model because the value is less than 15) compared other variations. There is a negative correlation for INTRUSION-MALWARE, BLOCKED-IGNORED, IGNORED-LOGGED, and LOW-MEDIUM. The predicted results for the next 12 months will increase starting from the second month at the same time. The resulting predictions can be used as a basis for policy and strategy decisions by stakeholders in dealing with fluctuations in cyber attacks that occur.
Strategic Evaluation of Whistleblower Software Security in Government: ISO/IEC 25010 and AHP Method Purbaratri, Winny; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Sistem Informasi Bisnis Vol 14, No 4 (2024): Volume 14 Nomor 4 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss4pp321-328

Abstract

To assess the effectiveness of software security measures in government whistleblower systems, we will utilize the ISO/IEC 25010 standard and the Analytic Hierarchy Process (AHP) methodology. Through the integration of various frameworks, our objective is to build a complete evaluation model that effectively identifies and enhances any vulnerabilities in these crucial systems. The strategy we employ combines the qualitative and quantitative evaluation capabilities of ISO/IEC 25010 and AHP, respectively, to offer a comprehensive perspective on software security performance. The results indicate substantial improvements in the security and reliability of whistleblower software, underscoring the effectiveness of our suggested evaluation technique in identifying crucial areas for refinement. Moreover, the utilization of AHP permitted the ranking of security qualities, guaranteeing focused and efficient improvements. Ultimately, the study emphasizes the significance of thorough security assessments for government whistleblower systems and verifies the effectiveness of utilizing ISO/IEC 25010 and AHP as a methodical approach to improve software security. This research enhances the ongoing endeavor to protect confidential data, fostering a more secure and reliable atmosphere for individuals who expose wrongdoing.
ANALISIS YURIDIS TENTANG PERLINDUNGAN TERHADAP KORBAN KEKERASAN DALAM RUMAH TANGGA (PUTUSAN NOMOR 1209/Pid.Sus/2021/PN.MEDAN) Setyawan, Iwan; Sinaga, Ester Ronida; Zalukhu, Pasrah; Sarumaha, Asisman
JURNAL DARMA AGUNG Vol 31 No 4 (2023): AGUSTUS
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Darma Agung (LPPM_UDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/ojsuda.v31i4.3563

Abstract

Kekerasan terhadap perempuan masalah yang sangat global yang tidak pernah terjadi habis untuk dibicarakan, dikarenakan pola kekerasan yang terjadi berulang-ulang terhadap korban kasus kekerasan dalam rumah tangga. Tujuan penelitian ini untuk mengetahui apa faktor-faktor menyebabkan terjadinya tindak pidana kekerasan dalam rumah tangga dan bagaimana perlindungan pada korban kekerasan dalam rumah tangga ditinjau dari Undang-Undang No 23 Tahun 2004, serta bagaimana perlindungan hukum bagi korban pada tindak pidana kekerasan dalam rumah tangga berdasarkan (Putusan No.1209/Pid.Sus/2021/PN.Medan). Metode penelitian ini menggunakan teknik pengumpulan kepustakaan atau (library research), yaitu buku-buku, putusan pengadilan, jurnal, dokumen-dokumen dan sumber teoritis lainnya untuk menyelesaikan permasalahan penelitian ini. Hasil penelitian ini adalah menganalisa faktor-faktor terjadinya kekerasan dalam rumah tangga, dan perlindungan pada korban kekerasan dalam rumah tangga ditinjau dari Undang- Undang No 23 Tahun 2004, perlindungan hukum bagi korban pada tindak pidana kekerasan dalam rumah tangga berdasarkan (Putusan No. 1209/Pid.Sus/2021/PN.Medan).
PENERAPAN WEBSITE DENGAN KONSEP ELECTRONIC TOURISM SUPPLY CHAIN DI DESA WISATA CURUG CILEMBER, DESA JOGJOGAN, CISARUA-BOGOR Gultom, Junias Robert; Setyawan, Iwan; Angellia, Filda; Laksono, Rudi; Romli, Romli
Jurnal Pengabdian Teratai Vol 5 No 2 (2024): Jurnal Pengabdian Teratai
Publisher : Lembaga Penelitian Dan Pengabdian Pada Masyarakat (LPPM) Institut Bisnis dan Informatika (IBI) Kosgoro 1957

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55122/teratai.v5i2.1400

Abstract

Tujuan: Kegiatan abdimas ini bertujuan untuk membantu pelaku UMKM di Desa Wisata Curug Cilember Desa Jogjogan, Cisarua, Bogor dalam mentransformasi dari kegiatan usaha secara konvensional ke digital. Metode: Program abdimas ini dilaksanakan melalui metode sosialisasi dan bimbingan teknis. Sosialisasi ditujukan bagi pelaku usaha agar menyadari pentingnya menguasai teknologi digital, sedangkan bimbingan teknis ditujukan bagi BUMDes sebagai Admin yang akan mengelola website. Kegiatan abdimas ini diawali dengan analisa kebutuhan pelaku usaha dan BUMDes terkait desain dan fitur-fitur yang dibutuhkan dalam website untuk memfasilitasi pelaku usaha dan BUMDes dalam mengelola pelaku usahan dan mengembangkan usahanya. Selanjutnya, setelah website selesai, kemudian diberikan penguatan pentingnya website bagi pelaku usaha dan bimbingan teknis bagi admin sebagai operator website. Hasil: Hasil dari abdimas ini berupa sebuah website dengan konsep the electronic tourism supply chain dan peningkatan kesadaran pelaku UMKM akan pentingnya mentransformasikan diri dari konvensional ke digital serta tata kelola UMKM oleh BUMDes. Kesimpulan: Melalui website, pelaku-pelaku usaha dari berbagai bidang usaha dapat diintegrasikan dan saling melengkapi dalam sebuah rantai pasok dari hulu ke hilir dalam meningkatkan pelayanan kepada pengunjung wisata di Curug Cilember.
PERENCANAAN PEMBANGKIT LISTRIK TENAGA SURYA YANG DIAPLIKASIKAN PADA MESIN EGG INCUBATOR KAPASITAS 960 TELUR UNGGAS Setyawan, Iwan; Sukoco, Septyan Eko Hardyan Saputra; Yulianto, Eko Susetyo; Trisno, Ramon
Jurnal Teknik Mesin (Journal Of Mechanical Engineering) Vol 11, No 1 (2022)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jtm.v11i1.14698

Abstract

Energi surya merupakan energi yang dapat dikonversi menjadi energi listrik. Pembangkit listrik yang memanfaatkan energi surya sebagai sumber penghasil listrik adalah Pembangkit Listrik Tenaga Surya (PLTS). Dimana alat utama untuk menangkap, mengubah, dan menghasilkan listrik adalah photovoltaic. Penelitian ini bertujuan untuk merancang dan studi kinerja sistem PLTS untuk diaplikasikan pada egg incubator kapasitas 960 telur unggas yang sudah diproduksi sebelumnya. Pada penelitian ini, perencanaan meliputi perhitungan komponen-komponen utama sistem PLTS. Komponen utama yang paling penting, photovoltaic digunakan jenis polikristal. Selanjutnya pengambilan data dilakukan di linkungan perumahan dengan menempatkan photovoltaic di atap rumah. Tegangan listrik yang dihasilkan bisa dibaca pada charge controller sedangkan hambatan listrik diukur menggunakan digital multimeter. Dari hasil penelitian, didapatkan hasil bahwa dengan daya yang dibutuhkan untuk mengoperasikan egg Incubator 2834 watt jam perhari , maka sistem membutuhkan 6 photovoltaic ukuran 100 WP. Kemudian baterai 12V-100 AH, dibutuhkan sebanyak 14 buah. Adapun charge controller dibutuhkan minimal 36 A, sedangkan inverter dibutuhkan daya minimal 200 watt. Pada analisa kinerja panel surya, daya maksimal terjadi pada jam 10 am. Pada jam ini 98,0 W dicapai pada kondisi cuaca cerah berawan. Disusul 95,22 W pada cuaca berawan, sedangkan cuaca cerah menghasilkan daya terendah 93,85 W. Adapun pada jam 16 pm, terjadi penurunan daya pada ketiga kondisi cuaca. Seperti pada jam 10 WIB, cuaca cerah menghasilkan daya terendah, yaitu 92,48 W. Namun demikian, dari hasil ini terlihat bahwa kinerja panel surya tidak menunjukkan penurunan kinerja secara sigifikan pada sepanjang hari untuk ketiga kondisi cuaca : cerah, cerah berawan dan berawan.
Network Intrusion Detection Using Transformer Models and Natural Language Processing for Enhanced Web Application Attack Detection Priatna, Wowon; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.82462

Abstract

The increasing frequency and complexity of web application attacks necessitate more advanced detection methods. This research explores integrating Transformer models and Natural Language Processing (NLP) techniques to enhance network intrusion detection systems (NIDS). Traditional NIDS often rely on predefined signatures and rules, limiting their effectiveness against new attacks. By leveraging the Transformer's ability to capture long-term dependencies and the contextual richness of NLP, this study aims to develop a more adaptive and intelligent intrusion detection framework. Utilizing the CSIC 2010 dataset, comprehensive preprocessing steps such as tokenization, stemming, lemmatization, and normalization were applied. Techniques like Word2Vec, BERT, and TF-IDF were used for text representation, followed by the application of the Transformer architecture. Performance evaluation using accuracy, precision, recall, F1 score, and AUC demonstrated the superiority of the Transformer-NLP model over traditional machine learning methods. Statistical validation through Friedman and T-tests confirmed the model's robustness and practical significance. Despite promising results, limitations include the dataset's scope, computational complexity, and the need for further research to generalize the model to other types of network attacks. This study indicates significant improvements in detecting complex web application attacks, reducing false positives, and enhancing overall security, making it a viable solution for addressing increasingly sophisticated cybersecurity threats
Exploring the Relationship between Artificial Intelligence and Business Performance Lutfiani, Ninda; Sembiring, Irwan; Setyawan, Iwan; Setiawan, Adi; Rahardja, Untung; Sulistio, Sulistio
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 1 (2025): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.86697

Abstract

The integration of Artificial Intelligence (AI) into business operations has garnered significant attention due to its potential impact on business performance. However, the relationship between AI adoption and business performance remains not fully understood. This article comprehensively analyzes this relationship through three key aspects: the acceptance and implementation of AI within organizations, the impact of AI on various dimensions of business performance, and the potential challenges associated with AI adoption. In this study, we employ SmartPLS as an analytical tool to evaluate the relationships between identified factors and the impact of AI adoption on business performance. Our findings reveal that several factors influence the adoption and implementation of AI, including data availability, organizational culture, leadership support, technical expertise, and ethical considerations. Moreover, AI adoption significantly influences business performance metrics such as productivity, efficiency, revenue, and customer satisfaction. Nonetheless, challenges arising from AI adoption, including shifts in job roles, data privacy, and security concerns, also require substantial attention. In conclusion, successful AI adoption and implementation necessitate careful consideration of organizational, technical, and ethical factors. This research provides valuable insights for business leaders and researchers seeking a deeper understanding of the relationship between Artificial Intelligence and business performance.
Analisis Yuridis Hukuman bagi Pelaku Tindak Pidana Perdagangan Orang (Studi Kasus Putusan Nomor 1318 Pk/Pid.sus/2023) Setyawan, Iwan; Simbolon, Winda C; Simanjuntak, Sarida Hotdeliana; Sembiring, Jenda Suranta
JUNCTO: Jurnal Ilmiah Hukum Vol 7, No 1 (2025): JUNCTO : Jurnal Ilmiah Hukum JUNI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/juncto.v7i1.6077

Abstract

Trafficking in persons is a transnational crime that violates human dignity and fundamental rights. This study analyzes the application of Law Number 21 of 2007 on the Eradication of Human Trafficking through a case study of Supreme Court Decision Number 1318 PK/Pid.Sus/2023. A normative juridical approach is employed to evaluate the legal grounds and judicial considerations in sentencing the perpetrator. The findings reveal that despite comprehensive legislation, its enforcement remains challenged by limited law enforcement capacity, evidentiary difficulties, and inadequate victim recovery mechanisms. The Supreme Court's ruling reflects legal consistency and rejects the judicial review due to the absence of valid new evidence (novum). This study recommends enhancing the capacity of legal practitioners and adopting a restorative justice approach to strengthen victim protection and improve sentencing effectiveness.
Deep Learning-Based Visualization of Network Threat Patterns Using GAN-Generated Infographic Wibowo, Mars Caroline; Setyawan, Iwan; Setiawan, Adi; Sembiring, Irwan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6717

Abstract

Despite the growing sophistication of cyberattacks, current network traffic analysis tools often lack intuitive visual support, limiting human analysts’ ability to interpret complex threat behaviors. To address this gap, this study proposes a novel deep learning-based visualization framework using a Deep Convolutional Generative Adversarial Network (DCGAN) to synthesize threat-specific infographics from structured numerical features in the CICIDS 2017 dataset. Unlike conventional methods, such as PCA or static dashboards, which often result in abstract or non-adaptive visuals, our approach generates class-distinct grayscale images that preserve the behavioral patterns of various attacks, including denial-of-service, brute force, and port scanning. The preprocessing pipeline reshapes the selected flow-based features into 28×28 matrices to train the generative model. Evaluation using the Frechet Inception Distance (FID) yielded a score of 28.4, whereas a CNN classifier trained on the generated images achieved 91.2% accuracy, confirming visual fidelity and semantic integrity. Additionally, a panel of human experts rated the interpretability of the generated images at 4.3 out of 5.0. These findings demonstrate that generative visualization can enhance human-centered threat analysis by bridging raw data with interpretable imagery, thereby offering a scalable and explainable approach for integrating AI into real-time security workflows.
Co-Authors Adi Setiawan Andreas A. Febrianto Andreas Ardian Febrianto Andreas Febrianto Apriansa, Farul April Lia Hananto Ardilla Ayu Dewanti Ridwan Arif Darmawan Baihaqi, Kiki Ahmad Bariski, Rezzi Nanda Danny Manongga Deddy Susilo Demas Sabatino Deny Christian Dhanar Intan Surya Saputra Eduard Royce Efraim Anggriyono Eko Sediyono Eva Yovita Dwi Utami Farica, Jevan Fauzi Ahmad Muda Fernanda, Denis Aditya Filda Angellia Florentina Tatrin Kurniati Fransiscus Dalu Setiaji Gunawan Dewantoro Hartanto Kusuma Wardana Henderi . Hendry Heri Setiawan Hindriyanto Dwi Purnomo Ignatius Agus Supriyono Ilham Hizbuloh Irwan Sembiring Ivanna Kristianti Timotius Joko Siswanto Jonatan, Jeany Johana Junias Robert Gultom Kevin Ananta Kuntadi Widiyoko Larasati, Dwira Kurnia Maria Enggar Santika Meilia, Kaizia Dwinta Millenika, Prayudha Mohammad Ridwan Ninda Lutfiani Onix Setyawan, Revivo Pratama, Rizky Dinar Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hendryanto Dwi Regina Lionnie Ridwan, Ridwan Romli Jumpai Panggabean Roy Rudolf Huizen Rudi Laksono Santoso, Joseph Teguh Santoso, Yosef Karuna Saptadi Nugroho Sarumaha, Asisman Sembiring, Jenda Suranta Septian Abednego Simanjuntak, Sarida Hotdeliana Simbolon, Winda C Sinaga, Ester Ronida Sirilus Widi Surya Pranata Sukoco, Septyan Eko Hardyan Saputra Sulistio Sulistio Theodorus Leo Hartono Theopillus J. H. Wellem Tri Mulyanto Tri Wahyuningsih Trisno Sri Suparyati Soenarto dan Dibyo Pramono Agung Wibowo Untung Rahardja Wibowo, Mars Caroline Winny purbaratri Yayi Suryo Prabandari Yulianto, Eko Susetyo Zainal Arifin Hasibuan Zalukhu, Pasrah